// Copyright (c) 2023 PaddlePaddle Authors. All Rights Reserved.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
//     http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.

#pragma once

#include "paddle/phi/core/dense_tensor.h"
#include "paddle/phi/core/device_context.h"
#include "paddle/phi/core/kernel_registry.h"

namespace phi {

template <typename T, typename Context>
void QuantizeLinearKernel(const Context& dev_ctx,
                          const DenseTensor& x,
                          const paddle::optional<DenseTensor>& scale,
                          const DenseTensor& zero_point,
                          const paddle::optional<DenseTensor>& in_accum,
                          const paddle::optional<DenseTensor>& in_state,
                          int quant_axis,
                          int bit_length,
                          int qmin,
                          int qmax,
                          int round_type,
                          bool is_test,
                          bool only_observer,
                          DenseTensor* out,
                          DenseTensor* out_state,
                          DenseTensor* out_accum,
                          DenseTensor* out_scale);

template <typename T, typename Context>
void DeQuantizeLinearKernel(const Context& dev_ctx,
                            const DenseTensor& x,
                            const paddle::optional<DenseTensor>& scale,
                            const DenseTensor& zero_point,
                            const paddle::optional<DenseTensor>& in_accum,
                            const paddle::optional<DenseTensor>& in_state,
                            int quant_axis,
                            int bit_length,
                            int qmin,
                            int qmax,
                            int round_type,
                            bool is_test,
                            bool only_observer,
                            DenseTensor* out,
                            DenseTensor* out_state,
                            DenseTensor* out_accum,
                            DenseTensor* out_scale);
template <typename T, typename Context>
void DeQuantizeLinearDeprecatedKernel(const Context& dev_ctx,
                                      const DenseTensor& x,
                                      const DenseTensor& in_scale,
                                      const DenseTensor& zero_point,
                                      int quant_axis,
                                      int bit_length,
                                      int qmin,
                                      int qmax,
                                      int round_type,
                                      bool only_observer,
                                      DenseTensor* out);
template <typename T, typename Context>
void QuantizeLinearDeprecatedTrainKernel(
    const Context& dev_ctx,
    const DenseTensor& x,
    const DenseTensor& in_scale,
    const DenseTensor& zero_point,
    const paddle::optional<DenseTensor>& in_accum,
    const paddle::optional<DenseTensor>& in_state,
    int quant_axis,
    int bit_length,
    int qmin,
    int qmax,
    int round_type,
    bool only_observer,
    DenseTensor* out,
    DenseTensor* out_state,
    DenseTensor* out_accum,
    DenseTensor* out_scale);
template <typename T, typename Context>
void QuantizeLinearDeprecatedInferKernel(const Context& dev_ctx,
                                         const DenseTensor& x,
                                         const DenseTensor& in_scale,
                                         const DenseTensor& zero_point,
                                         int quant_axis,
                                         int bit_length,
                                         int qmin,
                                         int qmax,
                                         int round_type,
                                         bool only_observer,
                                         DenseTensor* out);

}  // namespace phi
